Model comparison
GLM-4.7-Flash vs Qwen Max
GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 34.7 on the Noometry Index.
Last verified . 18 shared benchmarks.
Alibaba (Qwen)Summary
- They share 18 benchmarks with published results for both. GLM-4.7-Flash scores higher in 6 categories and Qwen Max in 2 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-4.7-Flash leads 36.1 to 22.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 58.3% for GLM-4.7-Flash and 16.1% for Qwen Max.
- GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $1.60 / $6.40 for Qwen Max.
- GLM-4.7-Flash accepts more context: 200K tokens versus 33K.
- GLM-4.7-Flash has downloadable open weights; the other is API-only.
Side by side
| GLM-4.7-Flash | Qwen Max | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 38.8 | 34.7 |
| Released | 2026-01-19 | 2024-04-03 |
| Weights | Open | Proprietary |
| Context window | 200K | 33K |
| Max output | 131K | 8K |
| Input $ / M tokens | $0.06 | $1.60 |
| Output $ / M tokens | $0.40 | $6.40 |
| Results tracked | 21 | 23 |
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Category by category
Coding GLM-4.7-Flash leads
GLM-4.7-Flash: 40.6 (#135), Qwen Max: 30.7 (#292)
| Benchmark | GLM-4.7-Flash | Qwen Max |
|---|---|---|
| LMArena Coding | 1383 | 1288 |
| Aider Polyglot | — | 21.8% |
Reasoning Qwen Max leads
GLM-4.7-Flash: 20.9 (#229), Qwen Max: 25.1 (#151)
| Benchmark | GLM-4.7-Flash | Qwen Max |
|---|---|---|
| LMArena Hard Prompts | 1356 | 1269 |
| Chess Puzzles | 0% | — |
Math GLM-4.7-Flash leads
GLM-4.7-Flash: 36.1 (#173), Qwen Max: 22.3 (#276)
| Benchmark | GLM-4.7-Flash | Qwen Max |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 58.3% | 16.1% |
| LMArena Math | 1355 | 1275 |
| MATH Level 5 | — | 67.2% |
| FrontierMath (Feb 2025 set) | — | 1% |
Knowledge GLM-4.7-Flash leads
GLM-4.7-Flash: 35.5 (#184), Qwen Max: 30.3 (#228)
| Benchmark | GLM-4.7-Flash | Qwen Max |
|---|---|---|
| GPQA Diamond | 60.5% | 56.1% |
| LMArena Expert | 1357 | 1248 |
| Vectara Hallucination Rate | 9.3% | — |
Multilingual GLM-4.7-Flash leads
GLM-4.7-Flash: 46.5 (#158), Qwen Max: 41.8 (#202)
| Benchmark | GLM-4.7-Flash | Qwen Max |
|---|---|---|
| LMArena Non-English | 1330 | 1263 |
| LMArena Chinese | 1403 | 1254 |
| LMArena French | 1332 | 1330 |
| LMArena German | 1337 | 1254 |
| LMArena Korean | 1283 | 1142 |
| LMArena Russian | 1332 | 1274 |
| LMArena Spanish | 1350 | 1290 |
| LMArena Japanese | — | 1205 |
Instruction Following GLM-4.7-Flash leads
GLM-4.7-Flash: 70.1 (#167), Qwen Max: 66.5 (#208)
| Benchmark | GLM-4.7-Flash | Qwen Max |
|---|---|---|
| LMArena Instruction Following | 1327 | 1262 |
Long Context GLM-4.7-Flash leads
GLM-4.7-Flash: 40.9 (#148), Qwen Max: 39.4 (#180)
| Benchmark | GLM-4.7-Flash | Qwen Max |
|---|---|---|
| LMArena Longer Query | 1345 | 1288 |
| Fiction.LiveBench | — | 66.7% |
Writing & Preference Too close to call
GLM-4.7-Flash: 47.4 (#210), Qwen Max: 47.8 (#205)
| Benchmark | GLM-4.7-Flash | Qwen Max |
|---|---|---|
| LMArena Text | 1351 | 1282 |
| LMArena Creative Writing | 1297 | 1248 |
| LMArena Multi-Turn | 1342 | 1277 |
| EQ-Bench Creative Writing | 1125 | — |
Frequently asked questions
Is GLM-4.7-Flash better than Qwen Max?
GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 34.7 on the Noometry Index.
Which is cheaper, GLM-4.7-Flash or Qwen Max?
GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; Qwen Max lists at $1.60 and $6.40.
Is GLM-4.7-Flash or Qwen Max better for coding?
GLM-4.7-Flash scores higher on coding benchmarks: 40.6 versus 30.7 in the Noometry coding category.
Which has the bigger context window?
GLM-4.7-Flash does, with 200K tokens against 33K.
How many benchmarks do GLM-4.7-Flash and Qwen Max share?
18 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Qwen Max has 23.